Latent Variable Models for Clustered Ordinal Data
Yinsheng Qu, Marion R. Piedmonte, SHARON VANDERBRUG MEDENDORP · Biometrics · 1995
Existing methods for the analysis of clustered, ordinal data are inappropriate for certain applications. We propose latent variable models for clustered ordinal data which are derived as natural extensions of latent variable models for clustered binary data (Qu, Williams, Beck, and Medendorp, 1992. Biometrics 48, 1095-1102). These models can be applied to repeated measures data, familial data, longitudinal data, and data with both cluster specific and occasion specific covariates with a wide range of correlation structures.